The control of autonomous driving systems is largely based on their visual predictions. However, due to the uncertainty and complexity of real-world driving environments, these systems will need to safely handle unfamiliar inputs. Otherwise, a misinterpretation of these inputs can lead to costly real-world misbehaviors. We examine the vision model… Read more
In recent years, Autonomous Underwater Vehicles (AUVs) have been in the forefront of oceanic research and exploration. Since some of these AUVs depend on visual input to move, interact with the environment, and communicate, it is important for them to make accurate generalizations about their visual observations. To better equip… Read more
Monitoring the water quality of lakes is a challenging task that can provide significant benefits and insights to environmental conservationists, policy-makers, and educators alike. While current methods utilize in-situ measurements to project water quality parameters, such methods are expensive and time consuming. This project proposes a Convolutional Neural Network regressor… Read more
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Music identification software has grown in popularity since the turn of the century, most notably with the release of Shazam and SoundHound. This technology is still incredibly relevant today, as Shazam was acquired by Apple in 2018. The general concept behind music identification is fairly straightforward: a user queries a… Read more
